Effects of the Translocation Status of Human Immunodeficiency Virus Type 1 Reverse Transcriptase on the Efficiency of Excision of Tenofovir
Bibliographic record
Abstract
The ATP-dependent phosphorolytic excision of nucleoside analogue reverse transcriptase inhibitors can diminish their inhibitory effects on human immunodeficiency virus replication. Previous studies have shown that excision can occur only when the reverse transcriptase complex exists in its pretranslocational state. Binding of the next complementary nucleotide causes the formation of a stable dead-end complex in the posttranslocational state, which blocks the excision reaction. To provide mechanistic insight into the excision of the acyclic phosphonate nucleotide analog tenofovir, we compared the efficiencies of the reaction in response to changes in the translocation status of the enzyme. We found that rates of excision of tenofovir with wild-type reverse transcriptase can be as high as those seen with 3'-azido-3'-deoxythymidine monophosphate (AZT-MP). Thymidine-associated mutations, which confer >100-fold and 3-fold decreased susceptibility to AZT and tenofovir, respectively, caused substantial increases in the efficiency of excision of both inhibitors. However, in contrast to the case for AZT-MP, the removal of tenofovir was highly sensitive to dead-end complex formation. Site-specific footprinting experiments revealed that complexes with AZT-terminated primers exist predominantly pretranslocation. In contrast, complexes with tenofovir-terminated primers are seen in both configurations. Low concentrations of the next nucleotide are sufficient to trap the complex posttranslocation despite the flexible, acyclic character of the compound. Thus, the relatively high rate of excision of tenofovir is partially neutralized by the facile switch to the posttranslocational state and by dead-end complex formation, which provides a degree of protection from excision in the cellular environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".